Python is a perfect language for creating simple PoC projects. We will not talk about the full list of Python’s advantages, but the most amazing one is that Python is cross platform. This feature is quite useful for building embedded system applications. No need to wait until a compiler builds binaries, no need to deploy applications to the board. And the same code runs on a PC desktop as well as on Linux-based boards like Raspberry Pi.
However, this approach has its limits. It cannot be used for some hardware-related projects, e.g. a PC desktop doesn’t have an SPI. And obviously ARM-based boards are slower than a PC. So in some cases an algorithm perfectly running on a desktop experiences a lack of performance on an embedded system.
Performance was critical in one of our latest projects (watch Amazon Alexa Virtual Device demo here). We used a Dragonboard 410c as one of target platforms. We were pleasantly surprised with the board’s performance. Even without instrumental benchmarking we felt a significant boost in OS packages installations, application launch, and overall performance compared to Raspberry Pi 3. Let's have a look at board specs:

Barcelona – February 22 - 25, 2016
For the second consecutive year DataArt will join Canonical at Mobile World Congress (MWC), the world’s largest gathering for the mobile industry, to demonstrate enterprise IoT solutions, big data, system integration and scalability.
DataArt will showcase the following IoT and cloud systems running on top of Canonical’s Ubuntu Snappy Core and Juju.

DataArt, in partnership with Microsoft and Canonical, hosted its first annual Open Source IoT Summit in New York City. On November 12, 2015, six dozen technology innovators gathered at Microsoft’s New York Conference Center on Times Square to learn how they can develop their own in-house IoT solutions.
DataArt has always been supporting open innovation movement, which is at the heart of new technology development, and our open source IoT device-management platform DeviceHive is a testament to that. DeviceHive runs on Canonical’s Ubuntu, is available on the Microsoft Azure Marketplace and provides the tools to solve any smart manufacturing or smart home challenge in-house, without costly investments in software solutions. At the summit, we showed how DeviceHive accelerates IoT product development, allows for creating a solution prototype in a matter of hours, and then deploying and scaling it to a limitless number of devices or control variables with no additional software or investments requirements.
We walked the audience through the design, prototyping, deployment, and scaling up of a predictive maintenance IoT solution, enabling preventative, condition-based monitoring of a piece of manufacturing equipment. We used accelerometer-based sensors and an IoT gateway to capture the vibration profile of a fan and analyzed it in the Microsoft Azure Cloud using Juju, to determine whether it’s in the range of a normally operating equipment, and if not – to trigger a maintenance alert.
Continuously monitoring manufacturing environments for hazards and having the option to prompt people (or even machines) to take corrective action to avoid damage or interruption, can significantly reduce manufacturing risks and costs. Device connectivity enables more than just monitoring and predictive maintenance, it ultimately allows for precise control and management of critical assets, automation of tasks and decision-making, and optimization of processes across the manufacturing value chain. That covers R&D, sourcing, production and outbound logistics which helps attain major reductions in waste, energy costs, and human intervention, leading to vast improvement in efficiency.
While manufacturing is the area where IoT is an obvious game changer, IoT presents a rich opportunity for all areas of our lives. Examples include a heart monitor implant that alerts care providers of important changes in a patient’s heart condition, a car with built-in sensors that alerts the owner’s phone when tire pressure becomes low or emissions high, or precision farming equipment with wireless links to data from satellites and ground sensors that adjusts the way each part of the field is farmed based on different soil and crop conditions. IoT can be used to build a home automation system that customizes home devices to the habits of its residents, eventually enabling smart cities: monitoring customers’ power usage behavior, managing power demand and supply to optimize city-wide electricity usage, enabling remote monitoring and maintenance of gas pipeline networks, or installing billboards that assess approaching human traffic and change display messages accordingly.
Connected devices are here to stay. Embracing the objects’ ability to sense their environment and communicate about it presents unprecedented opportunities and insight across industry sectors and processes. The greatest challenge ahead is learning to convert vast amounts of data into actionable insight, to make sense of complexity and respond to it swiftly, eventually enabling machine learning and minimizing human intervention. DataArt and its partners look forward to continued sharing of our experience with the IoT community. We welcome new partnerships to create value through new Internet-of-Things capabilities.

Hearing a lot about IoT lately? Want to learn everything from home automation to Industrial IoT? Want to try enterprise IoT solutions yourself? The Open Source IoT Summit is about open source IoT and Azure IoT solutions that anybody can use. Join Microsoft, Ubuntu / Canonical and DataArt to learn all about it and jointly start creating IoT solutions.Learn:

How to create and package enterprise IoT apps;

Monetizing IoT and selling IoT apps through IoT app stores;

IoT security;

Easily supporting different IoT standards;

How to connect IoT devices to the cloud and use Azure IoT services;

Open source tools to easily write and package IoT apps in any language;

DataArt, the maker of DeviceHive, and Canonical, the maker of Snappy, Ubuntu and Juju, present Open IoT Solutions on Azure Events.

DataArt and Canonical are demonstrating industrial preventive maintenance and home IoT scenarios, that can be prototyped, scaled, and deployed. DataArt’s DeviceHive running on Canonical’s Ubuntu VM, are available on the Microsoft Azure Marketplace, providing accessibility to a flexible IoT platform. New bundled IoT solutions and examples, DeviceHive on Snappy (RPii), Data Analytics stack deployed by Juju, and Microsoft Azure services, will be discussed and demonstrated.

The industrial Internet of Things (IoT) enables businesses to predict when industrial equipment is going to fail, so that action can be taken beforehand. A leader in this space, DataArt, developed one of the first IoT and big data open sourced platforms, DeviceHive, and published on the Microsoft Azure Marketplace.
DataArt has collaborated with Canonical, the company behind Ubuntu, as well as Microsoft.